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An Optimization Method of Steam Turbine Load Resilient Adjustment by Characterizing Dynamic Changes in Superheated Steam Energy

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  • Jiakui Shi

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
    Laboratory for Space Environment and Physical Sciences, Harbin Institute of Technology, Harbin 150001, China)

  • Shuangshuang Fan

    (School of Energy Science & Engineering, Harbin Institute of Technology, Harbin 150001, China)

  • Jiajia Li

    (School of Energy Science & Engineering, Harbin Institute of Technology, Harbin 150001, China)

  • Jiangnan Cheng

    (Laboratory for Space Environment and Physical Sciences, Harbin Institute of Technology, Harbin 150001, China)

  • Jie Wan

    (Laboratory for Space Environment and Physical Sciences, Harbin Institute of Technology, Harbin 150001, China
    School of Energy Science & Engineering, Harbin Institute of Technology, Harbin 150001, China)

  • Peng E

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
    Laboratory for Space Environment and Physical Sciences, Harbin Institute of Technology, Harbin 150001, China)

Abstract

Improving the dynamic regulation ability of thermal power units is effective for realizing flexible scheduling in modern power systems. At present, the unit regulation capacity is usually reflected by the load adjustment of the main steam pressure and flow tracking ability, through the calculation of the given and real-time deviation to complete the load, and by pressure adjustment. However, although the calculation involved in this method is easy and the results are intuitive, overshoot and lag can easily occur. The main reason for this is that the process from boiler combustion to turbine works has strong hysteresis and inertia, and the feedback signal of the pressure and flow rate cannot dynamically reflect the change in boiler combustion and steam energy. According to the heat transfer process of the unit, the main steam temperature can directly reflect the energy transfer in the furnace combustion process and then reflect the changing trend of steam energy. Analyzing the changing characteristics of the temperature, pressure, and flow of superheated steam under rapid load regulations makes it possible to calculate the instantaneous energy storage value of the main steam before the regulating valve, and this value was inserted into the coordinate system as a new feedforward signal. Finally, a simulation model was established by using the actual running data of the unit. A simulation experiment under variable working conditions demonstrated that this method could improve the dynamic adjustment of the unit to load and pressure and help the power grid absorb renewable energy.

Suggested Citation

  • Jiakui Shi & Shuangshuang Fan & Jiajia Li & Jiangnan Cheng & Jie Wan & Peng E, 2023. "An Optimization Method of Steam Turbine Load Resilient Adjustment by Characterizing Dynamic Changes in Superheated Steam Energy," Energies, MDPI, vol. 16(8), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3324-:d:1118839
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    References listed on IDEAS

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    1. Zhu, Mengshu & Li, Jinghua, 2022. "Integrated dispatch for combined heat and power with thermal energy storage considering heat transfer delay," Energy, Elsevier, vol. 244(PB).
    2. Malhotra, A. & Panda, D. M. R., 2001. "Thermodynamic properties of superheated and supercritical steam," Applied Energy, Elsevier, vol. 68(4), pages 387-393, April.
    3. Franco, Alessandro & Diaz, Ana R., 2009. "The future challenges for “clean coal technologies”: Joining efficiency increase and pollutant emission control," Energy, Elsevier, vol. 34(3), pages 348-354.
    4. Senegac[combining breve]nik, Andrej & Matija, Tuma, 1994. "Quick evaluation of the thermodynamic properties of water and steam," Applied Energy, Elsevier, vol. 49(4), pages 369-378.
    5. Fan, He & Zhang, Yu-fei & Su, Zhi-gang & Wang, Ben, 2017. "A dynamic mathematical model of an ultra-supercritical coal fired once-through boiler-turbine unit," Applied Energy, Elsevier, vol. 189(C), pages 654-666.
    6. Huang, Congzhi & Sheng, Xinxin, 2020. "Data-driven model identification of boiler-turbine coupled process in 1000 MW ultra-supercritical unit by improved bird swarm algorithm," Energy, Elsevier, vol. 205(C).
    7. Zhou, Hong & Chen, Cheng & Lai, Jingang & Lu, Xiaoqing & Deng, Qijun & Gao, Xingran & Lei, Zhongcheng, 2018. "Affine nonlinear control for an ultra-supercritical coal fired once-through boiler-turbine unit," Energy, Elsevier, vol. 153(C), pages 638-649.
    8. Zeng, Jimin & Liu, Lidong & Liang, Xiao & Chen, Shihe & Yuan, Jun, 2021. "Evaluating fuel consumption factor for energy conservation and carbon neutral on an industrial thermal power unit," Energy, Elsevier, vol. 232(C).
    9. Hou, Guolian & Gong, Linjuan & Hu, Bo & Huang, Ting & Su, Huilin & Huang, Congzhi & Zhou, Guiping & Wang, Shunjiang, 2022. "Flexibility oriented adaptive modeling of combined heat and power plant under various heat-power coupling conditions," Energy, Elsevier, vol. 242(C).
    10. Wang, Zhu & Liu, Ming & Yan, Junjie, 2021. "Flexibility and efficiency co-enhancement of thermal power plant by control strategy improvement considering time varying and detailed boiler heat storage characteristics," Energy, Elsevier, vol. 232(C).
    11. Liu, Ji-Zhen & Yan, Shu & Zeng, De-Liang & Hu, Yong & Lv, You, 2015. "A dynamic model used for controller design of a coal fired once-through boiler-turbine unit," Energy, Elsevier, vol. 93(P2), pages 2069-2078.
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